In silico prediction of the metabolism of Blastocrithidia nonstop, a trypanosomatid with non-canonical genetic code.

BACKGROUND: Almost all extant organisms use the same, so-called canonical, genetic code with departures from it being very rare. Even more exceptional are the instances when a eukaryote with non-canonical code can be easily cultivated and has its whole genome and transcriptome sequenced. This is the case of Blastocrithidia nonstop, a trypanosomatid flagellate that reassigned all three stop codons to encode amino acids. RESULTS: We in silico predicted the metabolism of B. nonstop and compared it with that of the well-studied human parasites Trypanosoma brucei and Leishmania major. The mapped mitochondrial, glycosomal and cytosolic metabolism contains all typical features of these diverse and important parasites. We also provided experimental validation for some of the predicted observations, concerning, specifically presence of glycosomes, cellular respiration, and assembly of the respiratory complexes. CONCLUSIONS: In an unusual comparison of metabolism between a parasitic protist with a massively altered genetic code and its close relatives that rely on a canonical code we showed that the dramatic differences on the level of nucleic acids do not seem to be reflected in the metabolisms. Moreover, although the genome of B. nonstop is extremely AT-rich, we could not find any alterations of its pyrimidine synthesis pathway when compared to other trypanosomatids. Hence, we conclude that the dramatic alteration of the genetic code of B. nonstop has no significant repercussions on the metabolism of this flagellate.

New Drinking Water Genome Catalog Identifies a Globally Distributed Bacterial Genus Adapted to Disinfected Drinking Water Systems.

Genome-resolved insights into the structure and function of the drinking water microbiome can advance the effective management of drinking water quality. To enable this, we constructed and curated thousands of metagenome-assembled and isolate genomes from drinking water distribution systems globally to develop a Drinking Water Genome Catalog (DWGC). The current DWGC disproportionately represents disinfected drinking water systems due to a paucity of metagenomes from nondisinfected systems. Using the DWGC, we identify core genera of the drinking water microbiome including a genus (UBA4765) within the order Rhizobiales that is frequently detected and highly abundant in disinfected drinking water systems. We demonstrate that this genus has been widely detected but incorrectly classified in previous amplicon sequencing-based investigations of the drinking water microbiome. Further, we show that a single genome variant (genomovar) within this genus is detected in 75% of drinking water systems included in this study. We propose a name for this uncultured bacterium as "Raskinella chloraquaticus" and describe the genus as "Raskinella" (endorsed by SeqCode). Metabolic annotation and modeling-based predictions indicate that this bacterium is capable of necrotrophic growth, is able to metabolize halogenated compounds, proliferates in a biofilm-based environment, and shows clear indications of disinfection-mediated selection.

From metagenomes to metabolism: Systematically assessing the metabolic flux feasibilities for "Candidatus Accumulibacter" species during anaerobic substrate uptake.

With the rapid growing availability of metagenome assembled genomes (MAGs) and associated metabolic models, the identification of metabolic potential in individual community members has become possible. However, the field still lacks an unbiassed systematic evaluation of the generated metagenomic information to uncover not only metabolic potential, but also feasibilities of these models under specific environmental conditions. In this study, we present a systematic analysis of the metabolic potential in species of "Candidatus Accumulibacter", a group of polyphosphate-accumulating organisms (PAOs). We constructed a metabolic model of the central carbon metabolism and compared the metabolic potential among available MAGs for "Ca. Accumulibacter" species. By combining Elementary Flux Modes Analysis (EFMA) with max-min driving force (MDF) optimization, we obtained all possible flux distributions of the metabolic network and calculated their individual thermodynamic feasibility. Our findings reveal significant variations in the metabolic potential among "Ca. Accumulibacter" MAGs, particularly in the presence of anaplerotic reactions. EFMA revealed 700 unique flux distributions in the complete metabolic model that enable the anaerobic uptake of acetate and its conversion into polyhydroxyalkanoates (PHAs), a well-known phenotype of "Ca. Accumulibacter". However, thermodynamic constraints narrowed down this solution space to 146 models that were stoichiometrically and thermodynamically feasible (MDF > 0 kJ/mol), of which only 8 were strongly feasible (MDF > 7 kJ/mol). Notably, several novel flux distributions for the metabolic model were identified, suggesting putative, yet unreported, functions within the PAO communities. Overall, this work provides valuable insights into the metabolic variability among "Ca. Accumulibacter" species and redefines the anaerobic metabolic potential in the context of phosphate removal. More generally, the integrated workflow presented in this paper can be applied to any metabolic model obtained from a MAG generated from microbial communities to objectively narrow the expected phenotypes from community members.

Effect of Seasonality on Microbiological Variability of Raw Cow Milk from Apulian Dairy Farms in Italy.

Raw cow milk is one of the most complex and unpredictable food matrices shaped by the interaction between biotic and abiotic factors. Changes in dairy farming conditions impact the quality and safety of milk, which largely depend on seasonality. Changes in microbiome composition and relative metabolic pathways are derived from microbial interactions, as well as from seasonality, mammary, and extramammary conditions (e.g., farm management and outdoor environment). Breeding data from >600 Apulian farms were examined, and the associated physicochemical parameters were processed by a reductionist approach to obtain a raw cow milk sample subset. We investigated the microbiological variability in cultivable and 16S rRNA sequencing microbiota as affected by seasonal fluctuations at two time points (winter and summer seasons). We identified families (Xanthomonadaceae, Enterobacteriaceae, and Pseudomonadaceae) whose increased abundance during winter may cause a shift toward a pathobiont microbial niche that leads to lower milk quality. Apulian summer season conditions were advantageous to the presence of specific taxa, i.e., Streptococcaceae (i.e., Lactococcus) and Limosilactobacillus fermentum, which in turn may favor better milk preservation. IMPORTANCE The strength of this study lies in the microbiological characterization of a wide range of farm management data to achieve a more comprehensive framework of Apulian milk. Specific regional pedoclimatic and management conditions impact the taxa present and their abundances within this ecological food niche. The obtained results lay the groundwork for comparison with other worldwide extensive farming areas.